2026-08-04

Internal Generation Record

Internal generation metadata: 296 candidate papers.

Published 2026-08-04 Target source 2026-08-02 Actual source 2026-07-31 Candidates 296 Featured 6 Tracked 20 Source date fallback

Generation Record

This page preserves selected papers, candidate scale, and source-date metadata for traceability. The page only changes presentation, not selected papers, ordering, or counts.

Internal generation record. Fetched at 2026-08-03T22:15:12.229600+00:00. Generated at 2026-08-03T22:16:19.717300+00:00. Machine-readable details stay under data/processed and data/reports.

Selected papers

RankTakeawayTopicarXiv
1make RAG retrieval and knowledge-base QA more reliableVision and Image Generation2607.28955
2make RAG retrieval and knowledge-base QA more reliableRetrieval and RAG2607.29527
3make RAG retrieval and knowledge-base QA more reliableBenchmarks and Evaluation2607.29462
4make agents use tools and reusable skills more reliablyAgents and Tool Use2607.29254
5make RAG retrieval and knowledge-base QA more reliableTraining and Post-training2607.29207
8strengthen multimodal understanding of charts, documents, and visual evidenceVideo Generation2607.29482
6make agents use tools and reusable skills more reliablyVision and Image Generation2607.29637
7make RAG retrieval and knowledge-base QA more reliableRetrieval and RAG2607.29491
9make RAG retrieval and knowledge-base QA more reliableVision and Image Generation2607.29370
10improve code generation, execution feedback, and automated repairTraining and Post-training2607.29202
11make agents use tools and reusable skills more reliablyAgents and Tool Use2607.29104
12improve code generation, execution feedback, and automated repairBenchmarks and Evaluation2607.29684
13make agents use tools and reusable skills more reliablyBenchmarks and Evaluation2607.29677
14improve model reasoning, planning, and verificationCode Intelligence2607.29586
15improve code generation, execution feedback, and automated repairCode Intelligence2607.29531
16improve code generation, execution feedback, and automated repairTraining and Post-training2607.29517
17make agents use tools and reusable skills more reliablyAgents and Tool Use2607.29516
18make agents use tools and reusable skills more reliablyAgents and Tool Use2607.29468
19improve code generation, execution feedback, and automated repairInterpretability2607.29463
20strengthen multimodal understanding of charts, documents, and visual evidenceMultimodal Models2607.29445
21make agents use tools and reusable skills more reliablyCode Intelligence2607.29422
22make agents use tools and reusable skills more reliablyAgents and Tool Use2607.29405
23make RAG retrieval and knowledge-base QA more reliableRetrieval and RAG2607.29402
24improve model reasoning, planning, and verificationBenchmarks and Evaluation2607.29401
25make agents use tools and reusable skills more reliablyBenchmarks and Evaluation2607.29377
26make agents use tools and reusable skills more reliablyRobotics and Embodied AI2607.29302